Why you don't create a mask to select only the points in array that
satisfies the condition on x and y coordinates. For example the code
below applies filter only to the values that have x coordinate bigger
than 0.7 and y coordinate smaller than 0.3:
mask = numpy.logical_and(points[:,0] > 0.7, points[:,1] < 0.3)
points = numpy.apply_along_axis(filter, axis = 1, arr = points[mask,:])
best,
Paulo
Em Seg, 2009-01-12 às 15:21 +0100, Eric LEBIGOT escreveu:
> Hello,
>> What is the fastest way of applying a function on a list of 2D points? More
> specifically, I have a list of 2D points, and some do not meet some criteria
> and must be rejected. Even more specifically, the filter only lets through
> points whose x coordinate satisfies some condition, _and_ whose y coordinates
> satisfies another condition (maybe is there room for optimization, here?).
>> Currently, I use
>> points = numpy.apply_along_axis(filter, axis = 1, arr = points)
>> but this creates a bottleneck in my program (array arr may contains 1 million
> points, for instance).
>> Is there anything that could be faster?
>> Any suggestion would be much appreciated!
>> EOL
>> _______________________________________________
> Numpy-discussion mailing list
>Numpy-discussion@scipy.org>http://projects.scipy.org/mailman/listinfo/numpy-discussion>